PyTuflow

Introduction

PyTUFLOW is a package of Python tools for extracting TUFLOW Classic and HPC time series results. It can be used to automate output tasks such as checking model health, goodness-of-fit for model calibration, viewing on-the-fly model output (used in conjunction with Write PO Online == ON), and high-volume output plotting from production runs.

For worked examples demonstrating the use of PyTUFLOW, please register for the free Introduction to Python for TUFLOW eLearning Course.

Installation

The PyTuflow library can be installed via Python's packaging manager (pip).
Open up the command prompt and enter the following:

python -m pip install pytuflow

If python is not on your system path, you can navigate to the folder containing the python.exe before trying to install PyTuflow
e.g.

cd c:\Python39
python -m pip install pytuflow

Class: ResData

Class for TUFLOW time series results.

Initialised as an empty object, or with results with a *.tpc in TUFLOW 2016 release and later or *.info in TUFLOW 2013 release.

import pytuflow


res = pytuflow.ResData()  # initialising as an empty object
# or
res = pytuflow.ResData('M01_5m_001.tpc')  # initialising with results

Methods

Method	Description	Returns
channelConnectionCount ( str Node ID )	Returns the number of channels connected to a given node	int Count
channelConnections ( str Node ID )	Returns a list of the channels connected to a given node	list Channel IDs
channelCount ()	Returns the total number of channels in results	int Count
channelResultTypes ()	Returns a list of all the available result types for channels	list of Result Types
channels ()	Returns a list of all the channels IDs in the results	list Channel IDs
channelsDownstream ( str Node ID )	Returns a list of all the channels downstream of a given node	list Channel IDs
channelsUpstream ( str Node ID )	Returns a list of all the channels upstream of a given node	list Channel IDs
format ()	Returns the result format i.e. '2013' or '2016'	str Format
getAdverseGradients ()	Returns locations of any adverse water level or energy level (if result type available) gradients in long profile. Note getLongProfileData method must be called prior to calling this method	tuple Adverse Water Level Gradient Locations ( list x data, list y data )
		tuple Adverse Energy Level Gradient Locations ( list x data, list y data )
getLongProfileData ( float Timestep, str Result Type, str Channel ID, [optional] str 2nd Channel ID )	Returns long profile data from a given channel to another channel. If no second channel is specified will continue until no further channels downstream	bool Error
		str Message
		tuple Profile Data ( list x values, list y values )
getLongProfileTimeOfMaximum ()	Returns the time of maximum water level along the current profile. Note getLongProfileData method must be called prior to calling this method	list x values
		list y values
getPipes ()	Returns any pipe or culvert data in the current profile. Note getLongProfileData method must be called prior to calling this method	list pipes [ list pipe vertexes [ tuple vertex ( x point, y point ) ] ]
getTimeSeriesData ( str Element, str Result Type, [optional] str domain )	Returns time series data for the given element (1D node, 1D channel, 2D PO, RL) for a the given result type. If there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements unless 'domain' variable is explicitly specified (domain options: '1D', '2D', 'RL')	bool Error
		str Message
		tuple time series data ( list x data, list y data )
load ( str Filepath )	Loads result file. File formats are *.tpc for TUFLOW release 2016 and later, or *.info for TUFLOW release 2013	bool Error
		str Message
longProfileResultTypes ()		list Result Types
maximum ( str Element, str Result Type, [optional] str Domain )	Returns the maximum result value for the given element (1D node, 1D channel, 2D PO, RL) for the given result type. If there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements unless 'domain' variable is explicitly specified (domain options: '1D', '2D', 'RL')	bool Error
		str Message
		float Maximum Value
maximumTimestepChange ( str Element, str Result Type, [optional] str Domain )	Returns the maximum change in result value in one timestep for the given element (RL elements supported only) for the given result type. If there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements unless 'domain' variable is explicitly specified (domain options: '1D', '2D', 'RL')	bool Error
		str Message
		float Maximum Value
name ()	Returns the name of the result	str Name
nodeCount ()	Returns the total number of nodes in the results	int Count
nodeDownstream ( str Channel ID )	Returns the name of the downstream node of a given channel	str Node ID
nodeResultTypes ()	Returns a list of all the available result types for nodes	list Result Types
nodes ()	Returns a list of all the node IDs in the results	list Node IDs
nodeUpstream ( str Channel ID )	Returns the name of the upstream node of a given channel	str Node ID
poNames ()	Returns a list of all the available Plot Output names	list PO ID
poResultTypes ()	Returns a list of all the available Plot Output result types	list Result Types
rlCount ()	Returns the total number of Reporting Locations (of all geometry type) in the results	int Count
rlLineCount ()	Returns the total number of line Reporting Locations in the results	int Count
rlNames ()	Returns a list of all the Reporting Location names	list RL ID
rlPointCount ()	Returns the total number of point Reporting Locations in the results	int Count
rlRegionCount ()	Returns the total number of region Reporting Locations in the results	int Count
rlResultTypes ()	Returns a list of all the available Reporting Location result types	list Result Types
source ()	Returns the full file path to the source result file (*.tpc or *.info)	str Path
timeOfMaximum ( str Element, str Result Type, [optional] str Domain )	Returns the time of maximum for the given element (1D node, 1D channel, 2D PO, RL) for the given result type. If there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements unless 'domain' variable is explicitly specified (domain options: '1D', '2D', 'RL')	bool Error
		str Message
		float Time (hrs)
timeOfMaximumTimestepChange ( str Element, str Result Type, [optional] str Domain )	Returns the time of maximum for change in result value in one timestep for the given element (RL elements supported only) for the given result type. If there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements unless 'domain' variable is explicitly specified (domain options: '1D', '2D', 'RL')	bool Error
		str Message
		float Time (hrs)

channelConnectionCount

channelConnectionCount ( Node ID )
Returns the number of channels connected to a given node

Parameters

Node ID: str

Name or ID of node e.g. 'Chan_A.1'

Returns

Count: int

Number of connected channels

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    node = 'Chan_A.1'
    conn_count = res.channelConnectionCount(node)
    # print to console    
    print('{0} channels connected to {1}'.format(conn_count, node))
else:
    # did not load correctly, print error message to console
    print(message)

channelConnections

channelConnections ( Node ID )
Returns a list of the channels connected to a given node

Parameters

Node ID: str

Name or ID of node e.g. 'Chan_A.1'

Returns

Out: list

List of connected channels e.g. ['Chan_A', 'Chan_B']

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    node = 'Chan_A.1'
    conn_chans = res.channelConnections(node)
    # print to console    
    print('Channels connected to {0}:'.format(node))
    for chan in conn_chans:
        print(chan)
else:
    # did not load correctly, print error message to console
    print(message)

channelCount

channelCount ()
Returns the total number of channels in results

Parameters

-

Returns

Count: int

Number of channels

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    chan_count = res.channelCount()
    # print to console    
    print('{0} channels in results'.format(chan_count))
else:
    # did not load correctly, print error message to console
    print(message)

channelResultTypes

channelResultTypes ()
Returns a list of all the available result types for channels

Parameters

-

Returns

Out: list

List of result types e.g. ['Q', 'V']

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    chan_rt = res.channelResultTypes()
    # print to console    
    print('Available channel result types:')
    for rt in chan_rt:
        print(rt)
else:
    # did not load correctly, print error message to console
    print(message)

channels

channels ()
Returns a list of all the channels IDs in the results

Parameters

-

Returns

Out: list

List of channels e.g. ['Chan_A', 'Chan_B', 'Chan_C']

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    chans = res.channels()
    # print to console    
    print('Channels:')
    for chan in chans:
        print(chan)
else:
    # did not load correctly, print error message to console
    print(message)

channelsDownstream

channelsDownstream ( Node ID )
Returns a list of all the channels downstream of a given node

Parameters

Node ID: str

Name or ID of node e.g. 'Chan_A.1'

Returns

Out: list

List of channels e.g. ['Chan_B']

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    node = 'Chan_A.1'
    dns_chans = res.channelsDownstream(node)
    # print to console    
    print('Channels downstream of {0}:'.format(node))
    for chan in dns_chans:
        print(chan)
else:
    # did not load correctly, print error message to console
    print(message)

channelsUpstream

channelsUpstream ( Node ID )
Returns a list of all the channels upstream of a given node

Parameters

Node ID: str

Name or ID of node e.g. 'Chan_A.1'

Returns

Out: list

List of channels e.g. ['Chan_A']

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    node = 'Chan_A.1'
    ups_chans = res.channelsUpstream(node)
    # print to console    
    print('Channels upstream of {0}:'.format(node))
    for chan in ups_chans:
        print(chan)
else:
    # did not load correctly, print error message to console
    print(message)

format

format ()
Returns the result format i.e. '2013' or '2016'

Parameters

-

Returns

Format: str

Format of results e.g. '2016'

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    format = res.format()
    # print to console    
    print('Results format: {0}'.format(format)
else:
    # did not load correctly, print error message to console
    print(message)

getAdverseGradients

getAdverseGradients ()
Returns locations of any adverse water level or energy level (if result type available) gradients in long profile. Note getLongProfileData method must be called prior to calling this method

Parameters

-

Returns

Adverse water level gradients: tuple

( list x data, list y data ) e.g. ([0, 5], [10, 12])

Adverse energy level gradients: tuple

( list x data, list y data ) e.g. ([0, 5], [11, 14])

Example

import matplotlib.pyplot as plt  # plotting library
import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before continuing
if not err:
    # initialise plot
    fig, ax = plt.subplots()

    # get long profiles and add to plot
    chan = 'Chan_A'
    timestep = 1.0
    result_types = ['Bed Level', 'H']  # get both water level and bed level
    for rt in result_types:
        err_lp, mess_lp, data = res.getLongProfileData(timestep, rt, chan)
    
        # check for error before plotting
        if not err_lp:
            x, y = data
            ax.plot(x, y, label=rt)
        else:
            # error occurred getting long profile data, print error message to console
            print(mess_lp)

    # check for adverse gradients
    adv = res.getAdverseGradients()
    for i, data in enumerate(adv):
        x, y = data

        # get appropriate label
        # getAdverseGradients() returns 2 datasets:
        # first dataset adverse water level
        # second dataset adverse energy level
        if i == 0:  # first dataset
            label = 'Adverse Water Levels'
        else:  # second dataset
            label = 'Adverse Energy Levels' 

        # add to plot as points
        ax.plot(x, y, label=label, marker='o', linestyle='None')
    
    # add legend to plot
    lines, labs = ax.get_legend_handles_labels()
    ax.legend(lines, labs)
      
    # show plot   
    fig.show()
else:
    # did not load correctly, print error message to console
    print(message)

getLongProfileData

getLongProfileData ( Timestep, Result Type, Channel ID, [optional] 2nd Channel ID )
Returns long profile data from a given channel to another channel. If no second channel is specified will continue until no further channels downstream

Parameters

Timestep: float or str

Output timestep to plot. Can be a value e.g. 1.5 or string e.g. 'max'

Result Type: str

Result type e.g. 'H'

Channel ID: str

Starting channel for long profile e.g. 'Chan_A'

2nd Channel ID: str

Optional downstream channel ID to stop the long profile at e.g. 'Chan_D'

Returns

Error: bool

Returns False on success, True when an error occurred

Message: str

Accompanying error message if an error occurred

Data: tuple

x data points: list

data point: float

y data points: list

data point: float

e.g. ([0, 1, 2, 3, 4, 5], [10, 20, 30, 20, 10, 0]

Example

import matplotlib.pyplot as plt  # plotting library
import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before continuing
if not err:
    # initialise plot
    fig, ax = plt.subplots()

    # get long profiles and add to plot
    chan = 'Chan_A'
    timestep = 1.0
    result_types = ['Bed Level', 'H']  # get both water level and bed level
    for rt in result_types:
        err_lp, mess_lp, data = res.getLongProfileData(timestep, rt, chan)
    
        # check for error before plotting
        if not err_lp:
            x, y = data
            ax.plot(x, y, label=rt)
        else:
            # error occurred getting long profile data, print error message to console
            print(mess_lp)

    # add legend to plot
    lines, labs = ax.get_legend_handles_labels()
    ax.legend(lines, labs)
      
    # show plot   
    fig.show()
else:
    # did not load correctly, print error message to console
    print(message)

getLongProfileTimeOfMaximum

getLongProfileTimeOfMaximum ()
Returns the time of maximum water level along the current profile. Note getLongProfileData method must be called prior to calling this method

Parameters

-

Returns

x data: list

x points for plotting time of max along long profile e.g. [0, 1, 2, 3, 4, 5]

y data: list

y points for plotting time of max along long profile e.g. [10, 11, 12, 13, 14, 15]

Example

import matplotlib.pyplot as plt  # plotting library
import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before continuing
if not err:
    # initialise plot
    fig, ax = plt.subplots()

    # get long profiles and add to plot
    chan = 'Chan_A'
    timestep = 'max'  # maximum result along profile
    result_types = ['Bed Level', 'H']  # get both water level and bed level
    for rt in result_types:
        err_lp, mess_lp, data = res.getLongProfileData(timestep, rt, chan)
    
        # check for error before plotting
        if not err_lp:
            x, y = data
            ax.plot(x, y, label=rt)
        else:
            # error occurred getting long profile data, print error message to console
            print(mess_lp)

    # also plot time of max water level on secondary axis
    tom_x, tom_y = res.getLongProfileTimeOfMaximum()
    ax2 = ax.twinx()  # initialise secondary axis

    # add to plot on secondary axis
    ax2.plot(tom_x, tom_y, label='Time of Maximum', linestyle='--')
    
    # combine axis legends and add to plot
    lines, labs = ax.get_legend_handles_labels()
    lines2, labs2 = ax2.get_legend_handles_labels()
    comb_lines = lines + lines2
    comb_labs = labs + labs2
    ax.legend(comb_lines, comb_labs)
      
    # show plot   
    fig.show()
else:
    # did not load correctly, print error message to console
    print(message)

getPipes

getPipes ()
Returns any pipe or culvert data in the current profile. Note getLongProfileData method must be called prior to calling this method

Parameters

-

Returns

Pipe list: list

Vertex list: list

Vertex coords: tuple

e.g. [[(0, 0), (0, 1), (1, 1), (1, 0)], [(1, 1), (1, 2), (2, 2), (2, 1)]]

Example

import matplotlib.pyplot as plt  # plotting library
from matplotlib.patches import Polygon  # will add pipes and culverts as polygon
import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before continuing
if not err:
    # initialise plot
    fig, ax = plt.subplots()

    # get long profiles and add to plot
    chan = 'Chan_A'
    timestep = 1.0
    result_types = ['Bed Level', 'H']  # get both water level and bed level
    for rt in result_types:
        err_lp, mess_lp, data = res.getLongProfileData(timestep, rt, chan)
    
        # check for error before plotting
        if not err_lp:
            x, y = data
            ax.plot(x, y, label=rt)
        else:
            # error occurred getting long profile data, print error message to console
            print(mess_lp)

    # get pipes and culverts and add to plot
    pipes = res.getPipes()
    for pipe in pipes:  # loop through all pipes
        polygon = Polygon(pipe, facecolor='0.9', edgecolor='0.5', label='Culverts and Pipes')
        ax.add_patch(polygon)
    
    # add legend to plot
    lines, labs = ax.get_legend_handles_labels()

    # filter duplicate legend items 
    # for example if there is more than one pipe or culvert we only want that to appear once in the legend
    unique_lines = []
    unique_labels = []
    for i, label in enumerate(labs):
        if label not in unique_labels:
            unique_labels.append(label)
            unique_lines.append(lines[i])
    ax.legend(unique_lines, unique_labels)
      
    # show plot   
    fig.show()
else:
    # did not load correctly, print error message to console
    print(message)

getTimeSeriesData

getTimeSeriesData ( Element, Result Type, [optional] domain )
Returns time series data for the given element (1D node, 1D channel, 2D PO, RL) for a the given result type. If there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements unless 'domain' variable is explicitly specified (domain options: '1D', '2D', 'RL')

Parameters

Element: str

Channel, Node, PO, or RL element to get time series data for

Result Type: str

Result type e.g. 'H'

Domain: str

Optional input to specify which domain the Element belongs in. If left as default (None) and there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements.

Returns

Error: bool

Returns False on success, True when an error occurred

Message: str

Accompanying error message if an error occurred

Data: tuple

x data points: list

y data points: list

e.g. ([0, 1, 2, 3, 4, 5], [10, 20, 30, 20, 10, 0]

Examples
Plotting results for multiple elements on the same graph

import matplotlib.pyplot as plt  # plotting library
import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before continuing
if not err:
    # initialise plot
    fig, ax = plt.subplots()

    # get time series data and add to plot
    elements = ['Chan_A', 'Chan_B', 'Chan_C']
    result_type = 'Q'
    for element in elements:
        err_ts, mess_ts, data = res.getTimeSeriesData(element, result_type)
    
        # check for error before plotting
        if not err_ts:
            x, y = data
            ax.plot(x, y, label=element)
        else:
            # error occurred getting time series data, print error message to console
            print(mess_ts)
    
    # add legend to plot
    lines, labs = ax.get_legend_handles_labels()
    ax.legend(lines, labs)
      
    # show plot   
    fig.show()
else:
    # did not load correctly, print error message to console
    print(message)

Plotting water level and velocity on the same plot using a secondary axis

import matplotlib.pyplot as plt  # plotting library
import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before continuing
if not err:
    # initialise plot
    fig, ax = plt.subplots()
    # initialise secondary axis
    ax2 = ax.twinx()

    # get time series data and add to plot
    elements = ['Chan_A', 'Chan_B', 'Chan_C']
    result_types = ['Q', 'V']
    for element in elements:
        for result_type in result_types:
            err_ts, mess_ts, data = res.getTimeSeriesData(element, result_type)
    
            # check for error before plotting
            if not err_ts:
                x, y = data
                label = '{0}: {1}'.format(result_type, element)

                # plot Q on first axis, V on secondary axis
                if result_type == 'Q':
                    # first axis
                    ax.plot(x, y, label=label)
                else:  # must be 'V'
                    # secondary axis
                    ax2.plot(x, y, label=label, linestyle='--')
            else:
                # error occurred getting time series data, print error message to console
                print(mess_ts)
    
    # combine primary and secondary axis items and add to legend
    lines, labs = ax.get_legend_handles_labels()
    lines2, labs2 = ax2.get_legend_handles_labels()
    lines_comb = lines + lines2
    labs_comb = labs + labs2
    ax.legend(lines_comb, labs_comb)
      
    # show plot   
    fig.show()
else:
    # did not load correctly, print error message to console
    print(message)

Saving a separate plot for each element as a *.png

import os  # library for operating system file and directory manipulation
import matplotlib.pyplot as plt  # plotting library
import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# save directory for figures
save_dir = r'C:TUFLOW\results\figures'

# check results were loaded successfully before continuing
if not err:
    # get time series data and add to plot
    elements = ['Chan_A', 'Chan_B', 'Chan_C']
    result_type = 'Q'
    for element in elements:
        err_ts, mess_ts, data = res.getTimeSeriesData(element, result_type)
    
        # check for error before plotting
        if not err_ts:
            # initialise plot
            fig, ax = plt.subplots()
            x, y = data
            ax.plot(x, y, label=element)
            
            # add legend to plot
            lines, labs = ax.get_legend_handles_labels()
            ax.legend(lines, labs)

            # add axis labels
            ax.set_xlabel('Time (hrs)')
            ax.set_ylabel('Flow (m3/s)')

            # save fig
            save_name = 'Figure_{0}_{1}.png'.format(element, result_type)
            save_path = os.path.join(save_dir, save_name)
            fig.savefig(save_path)

        else:
            # error occurred getting time series data, print error message to console
            print(mess_ts)
else:
    # did not load correctly, print error message to console
    print(message)

load

load ( Filepath )
Loads result file. File formats are *.tpc for TUFLOW release 2016 and later, or *.info for TUFLOW release 2013

Parameters

Filepath: str

Full path to *.tpc or *.info

Returns

Error: bool

Returns False on success, returns True if an error occurred

Message: str

Accompanying error message if an error occurs

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check if an error occurred
if err:
    # print message
    print(message)

longProfileResultTypes

longProfileResultTypes ()
Returns list of available long profile result types

Parameters

-

Returns

out: list

List of available result types for long profile plotting

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    lp_rt = res.longProfileResultTypes()
    # print to console    
    print('Available long profile result types:')
    for rt in lp_rt:
        print(rt)
else:
    # did not load correctly, print error message to console
    print(message)

maximum

maximum ( Element, Result Type, [optional] Domain )
Returns the maximum result value for the given element (1D node, 1D channel, 2D PO, RL) for the given result type. If there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements unless 'domain' variable is explicitly specified (domain options: '1D', '2D', 'RL')

Parameters

Element: str

Channel, Node, or RL element to get maximum result for. PO results do not currently support getting maximum value.

Result Type: str

Result type e.g. 'H'

Domain: str

Optional input to specify which domain the Element belongs in. If left as default (None) and there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements.

Returns

Error: bool

Returns False on success, True when an error occurred

Message: str

Accompanying error message if an error occurred

Maximum float

Maximum result

Examples
Maximum flow in a channel

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    channel = 'Chan_A'
    maximum = res.maximum(channel, 'Q')
    # print to console    
    print('Max flow at {0} is {1} m3/s'.format(channel, maximum)
else:
    # did not load correctly, print error message to console
    print(message)

Maximum water level at a node

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    node = 'Chan_A.1'
    maximum = res.maximum(channel, 'H')
    # print to console    
    print('Max water level at {0} is {1} mRL'.format(node, maximum)
else:
    # did not load correctly, print error message to console
    print(message)

maximumTimestepChange

maximumTimestepChange ( Element, Result Type, [optional] Domain )
Returns the maximum change in result value in one timestep for the given element (RL elements supported only) for the given result type. If there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements unless 'domain' variable is explicitly specified (domain options: '1D', '2D', 'RL')

Parameters

Element: str

RL element to get maximum change in a single timestep for. Currently RL elements are the only supported type.

Result Type: str

Result type e.g. 'H'

Domain: str

Optional input to specify which domain the Element belongs in. If left as default (None) and there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements.

Returns

Error: bool

Returns False on success, True when an error occurred

Message: str

Accompanying error message if an error occurred

Maximum float

Maximum value change in any given timestep

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    loc = 'Reporting Location 1'
    tsMaximum = res.maximumTimestepChange(channel, 'Q')
    # print to console    
    print('Max flow change in any given timestep at {0} is {1} m3/s'.format(loc, tsMaximum)
else:
    # did not load correctly, print error message to console
    print(message)

name

name ()
Returns the name of the result

Parameters

-

Returns

Name: str

Name of results

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    name = res.name()
    # print to console    
    print('Results from {0} loaded successfully.format(name))
else:
    # did not load correctly, print error message to console
    print(message)

nodeCount

nodeCount ()
Returns the total number of nodes in the results

Parameters

-

Returns

Count: int

Number of nodes

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    node_count = res.nodeCount()
    # print to console    
    print('{0} nodes in results.format(node_count))
else:
    # did not load correctly, print error message to console
    print(message)

nodeDownstream

nodeDownstream ( Channel ID )
Returns the name of the downstream node of a given channel

Parameters

Channel ID: str

Name or ID of channel

Returns

Node ID: str

Name or ID of downstream node

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    channel = 'Chan_A'
    dns_node = res.nodeDownstream(channel)
    # print to console    
    print('Downstream node of channel {0} is {1}'.format(channel, dns_node))
else:
    # did not load correctly, print error message to console
    print(message)

nodeResultTypes

nodeResultTypes ()
Returns a list of all the available result types for nodes

Parameters

-

Returns

Out: list

List of available result types for nodes e.g. ['H', 'E']

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    result_types = res.nodeResultTypes()
    # print to console    
    print('Available result types for nodes are:)
    for result_type in result_types:
        print(result_type)
else:
    # did not load correctly, print error message to console
    print(message)

nodes

nodes ()
Returns a list of all the node IDs in the results

Parameters

-

Returns

Out: list

List of all nodes names in results e.g. ['Chan_A.1', 'Chan_A.2', 'Chan_B.2', 'Chan_C.2'...]

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    nodes = res.nodes()
    # print to console    
    print('Nodes:)
    for node in nodes:
        print(node)
else:
    # did not load correctly, print error message to console
    print(message)

nodeUpstream

nodeUpstream ( Channel ID )
Returns the name of the upstream node of a given channel

Parameters

Channel ID: str

Name or ID of channel

Returns

Node ID: str

Name or ID of upstream node

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    channel = 'Chan_A'
    ups_node = res.nodeUpstream(channel)
    # print to console    
    print('Upstream node of channel {0} is {1}'.format(channel, ups_node))
else:
    # did not load correctly, print error message to console
    print(message)

poNames

poNames ()
Returns a list of all the available Plot Output names

Parameters

-

Returns

Out: list

List of all PO names in results e.g. ['Loc_1', 'Loc_2', 'Loc_3']

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    po_names = res.poNames()
    # print to console    
    print('PO Names:)
    for po_name in po_names:
        print(po_name)
else:
    # did not load correctly, print error message to console
    print(message)

poResultTypes

poResultTypes ()
Returns a list of all the available Plot Output result types

Parameters

-

Returns

Out: list

List of available result types for Plot Outputs e.g. ['Q', 'H', 'V']

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    result_types = res.poResultTypes()
    # print to console    
    print('Available result types for Plot Outputs are:)
    for result_type in result_types:
        print(result_type)
else:
    # did not load correctly, print error message to console
    print(message)

rlCount

rlCount ()
Returns the total number of Reporting Locations (of all geometry type) in the results

Parameters

-

Returns

Count: int

Number of RL objects

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    rl_count = res.rlCount()
    # print to console    
    print('{0} RL objects in results.format(node_count))
else:
    # did not load correctly, print error message to console
    print(message)

rlLineCount

rlLineCount ()
Returns the total number of line Reporting Locations in the results

Parameters

-

Returns

Count: int

Number of RL Line objects

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    rl_line_count = res.rlLineCount()
    # print to console    
    print('{0} RL Line objects in results.format(node_line_count))
else:
    # did not load correctly, print error message to console
    print(message)

rlNames

rlNames ()
Returns a list of all the Reporting Location names

Parameters

-

Returns

Out: list

List of all RL names in results e.g. ['Reporting_Loc_1', 'Reporting_Loc_2', 'Reporting_Loc_3']

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    rl_names = res.rlNames()
    # print to console    
    print('RL Names:)
    for rl_name in rl_names:
        print(rl_name)
else:
    # did not load correctly, print error message to console
    print(message)

rlPointCount

rlPointCount ()
Returns the total number of point Reporting Locations in the results

Parameters

-

Returns

Count: int

Number of RL Point objects

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    rl_point_count = res.rlPointCount()
    # print to console    
    print('{0} RL Point objects in results.format(node_point_count))
else:
    # did not load correctly, print error message to console
    print(message)

rlRegionCount

rlRegionCount ()
Returns the total number of region Reporting Locations in the results

Parameters

-

Returns

Count: int

Number of RL Region objects

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    rl_region_count = res.rlRegionCount()
    # print to console    
    print('{0} RL Region objects in results.format(node_region_count))
else:
    # did not load correctly, print error message to console
    print(message)

rlResultTypes

rlResultTypes ()
Returns a list of all the available Reporting Location result types

Parameters

-

Returns

Out: list

List of available result types for Reporting Locations e.g. ['Q', 'H', 'Vol']

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    result_types = res.rlResultTypes()
    # print to console    
    print('Available result types for Reporting Locations are:)
    for result_type in result_types:
        print(result_type)
else:
    # did not load correctly, print error message to console
    print(message)

source

source ()
Returns the full file path to the source result file (*.tpc or *.info)

Parameters

-

Returns

Source: str

Full path to result file

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    source = res.source()
    # print to console    
    print('Successfully loaded result from {0}.format(source))
else:
    # did not load correctly, print error message to console
    print(message)

timeOfMaximum

timeOfMaximum ( Element, Result Type, [optional] Domain )
Returns the time of maximum for the given element (1D node, 1D channel, 2D PO, RL) for the given result type. If there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements unless 'domain' variable is explicitly specified (domain options: '1D', '2D', 'RL')

Parameters

Element: str

Channel, Node, or RL element to get maximum result for. PO results do not currently support getting time of maximum.

Result Type: str

Result type e.g. 'H'

Domain: str

Optional input to specify which domain the Element belongs in. If left as default (None) and there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements.

Returns

Error: bool

Returns False on success, True when an error occurred

Message: str

Accompanying error message if an error occurred

Time of Maximum: float

Time of maximum

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    node = 'Chan_A.1'
    tom = res.timeOfMaximum(channel, 'H')
    # print to console    
    print('Time of max water level at {0} is {1} hrs'.format(channel, tom)
else:
    # did not load correctly, print error message to console
    print(message)

timeOfMaximumTimestepChange

timeOfMaximumTimestepChange ( Element, Result Type, [optional] Domain )
Returns the time of maximum for change in result value in one timestep for the given element (RL elements supported only) for the given result type. If there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements unless 'domain' variable is explicitly specified (domain options: '1D', '2D', 'RL')

Parameters

Element: str

RL element to get time of maximum change in a single timestep for. Currently RL elements are the only supported type.

Result Type: str

Result type e.g. 'H'

Domain: str

Optional input to specify which domain the Element belongs in. If left as default (None) and there are duplicate names between 1D, PO, or RL elements it will give priority return to 1D elements first, PO elements second, and lastly RL elements.

Returns

Error: bool

Returns False on success, True when an error occurred

Message: str

Accompanying error message if an error occurred

Maximum float

Time of maximum value change

Example

import pytuflow

# Initialise result class
res = pytuflow.ResData()

# load .tpc result file
path = r'C:\TUFLOW\results\M04_5m_001.tpc'
err, message = res.load(path)

# check results were loaded successfully before calling function
if not err:
    loc = 'Reporting Location 1'
    tom_ts = res.timeOfMaximumTimestepChange(channel, 'Q')
    # print to console    
    print('Time of max flow change in any given timestep at {0} is {1} hrs'.format(loc, tom_ts)
else:
    # did not load correctly, print error message to console
    print(message)